Editorial Type:
Article
Article Type:
Research Article

A Nonparametric Multivariate Multi-Index Drought Monitoring Framework

Zengchao Hao University of California, Irvine, Irvine, California

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Amir AghaKouchak University of California, Irvine, Irvine, California

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Print Publication:
01 Feb 2014
Collections:
Advancing Drought Monitoring and Prediction
DOI:
https://doi.org/10.1175/JHM-D-12-0160.1
Page(s):
89–101
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Abstract

Accurate and reliable drought monitoring is essential to drought mitigation efforts and reduction of social vulnerability. A variety of indices, such as the standardized precipitation index (SPI), are used for drought monitoring based on different indicator variables. Because of the complexity of drought phenomena in their causation and impact, drought monitoring based on a single variable may be insufficient for detecting drought conditions in a prompt and reliable manner. This study outlines a multivariate, multi-index drought monitoring framework, namely, the multivariate standardized drought index (MSDI), for describing droughts based on the states of precipitation and soil moisture. In this study, the MSDI is evaluated against U.S. Drought Monitor (USDM) data as well as the commonly used standardized indices for drought monitoring, including detecting drought onset, persistence, and spatial extent across the continental United States. The results indicate that MSDI includes attractive properties, such as higher probability of drought detection, compared to individual precipitation and soil moisture–based drought indices. This study shows that the MSDI leads to drought information generally consistent with the USDM and provides additional information and insights into drought monitoring.

Corresponding author address: Amir AghaKouchak, Department of Civil and Environmental Engineering, University of California, Irvine, E4130 Engineering Gateway, Irvine, CA 92697-2175. E-mail: amir.a@uci.edu

This article is included in the Advancing Drought Monitoring and Prediction Special Collection.

Abstract

Accurate and reliable drought monitoring is essential to drought mitigation efforts and reduction of social vulnerability. A variety of indices, such as the standardized precipitation index (SPI), are used for drought monitoring based on different indicator variables. Because of the complexity of drought phenomena in their causation and impact, drought monitoring based on a single variable may be insufficient for detecting drought conditions in a prompt and reliable manner. This study outlines a multivariate, multi-index drought monitoring framework, namely, the multivariate standardized drought index (MSDI), for describing droughts based on the states of precipitation and soil moisture. In this study, the MSDI is evaluated against U.S. Drought Monitor (USDM) data as well as the commonly used standardized indices for drought monitoring, including detecting drought onset, persistence, and spatial extent across the continental United States. The results indicate that MSDI includes attractive properties, such as higher probability of drought detection, compared to individual precipitation and soil moisture–based drought indices. This study shows that the MSDI leads to drought information generally consistent with the USDM and provides additional information and insights into drought monitoring.

Corresponding author address: Amir AghaKouchak, Department of Civil and Environmental Engineering, University of California, Irvine, E4130 Engineering Gateway, Irvine, CA 92697-2175. E-mail: amir.a@uci.edu

This article is included in the Advancing Drought Monitoring and Prediction Special Collection.

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